keras3 1.0.0
-
Chains of
layer_*
calls with|>
now instantiate layers in the
same order as%>%
pipe chains: left-hand-side first (#1440). -
iterate()
,iter_next()
andas_iterator()
are now reexported from reticulate.
User facing changes with upstream Keras v3.3.3:
-
new functions:
op_slogdet()
,op_psnr()
-
clone_model()
gains new args:call_function
,recursive
Updated example usage. -
op_ctc_decode()
strategy argument has new default:"greedy"
.
Updated docs. -
loss_ctc()
default name fixed, changed to"ctc"
User facing changes with upstream Keras v3.3.2:
-
new function:
op_ctc_decode()
-
new function:
op_eigh()
-
new function:
op_select()
-
new function:
op_vectorize()
-
new function:
op_image_rgb_to_grayscale()
-
new function:
loss_tversky()
-
new args:
layer_resizing(pad_to_aspect_ratio, fill_mode, fill_value)
-
new arg:
layer_embedding(weights)
for providing an initial weights matrix -
new args:
op_nan_to_num(nan, posinf, neginf)
-
new args:
op_image_resize(crop_to_aspect_ratio, pad_to_aspect_ratio, fill_mode, fill_value)
-
new args:
op_argmax(keepdims)
andop_argmin(keepdims)
-
new arg:
clear_session(free_memory)
for clearing without invoking the garbage collector. -
metric_kl_divergence()
andloss_kl_divergence()
clip inputs
(y_true
andy_pred
) to the[0, 1]
range. -
new
Layer()
attributes:metrics
,dtype_policy
-
Added initial support for float8 training
-
layer_conv_*d()
layers now support LoRa -
op_digitize()
now supports sparse tensors. -
Models and layers now return owned metrics recursively.
-
Add pickling support for Keras models. (e.g., via
reticulate::py_save_object()
)
Note that pickling is not recommended, prefer using Keras saving APIs.